Instructions to use hf-internal-testing/tiny-random-Blip2ForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Blip2ForConditionalGeneration with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="hf-internal-testing/tiny-random-Blip2ForConditionalGeneration")# Load model directly from transformers import AutoProcessor, AutoModelForVisualQuestionAnswering processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-Blip2ForConditionalGeneration") model = AutoModelForVisualQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-Blip2ForConditionalGeneration") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec15c6095be59c9b3ad64705865f920d3b180c1fcaa5d80de582e433b459122e
- Size of remote file:
- 899 kB
- SHA256:
- e84aa733ff9bae4936c6190d73fc6bd236749f57db51428a7208a4bd30d6a9a5
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